Timeline for How would you explain Moment Generating Function(MGF) in layman's terms?
Current License: CC BY-SA 4.0
10 events
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| Jun 15, 2022 at 17:52 | history | edited | Michael Hardy | CC BY-SA 4.0 |
Sizes of delimiters and other copy-editing.
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| May 3, 2020 at 14:53 | comment | added | Aksakal | @Aerin this isn’t the proof but you could do the following. Start with the moments that you calculated from PDF. Then plug these into Taylor expansion as its coefficients. If this renders a function then it is MGF. By construction it contains all moments. | |
| Apr 30, 2020 at 21:04 | comment | added | kjetil b halvorsen♦ | @aerin: If you can reconstruct the pdf from the pdf, then everything you can calculate from the pdf can be calculated from the mgf. So for a proof you need to find such a reconstruction formula ... | |
| Sep 16, 2019 at 4:21 | comment | added | aerin | How can we prove that MGF & PDF contain the same amount of information? | |
| Jan 25, 2019 at 21:15 | comment | added | ColorStatistics | @whuber: Thank you, whuber. I'll study that reference. This is a topic I am looking to understand better. | |
| Jan 25, 2019 at 20:27 | comment | added | whuber♦ | To appreciate the point made by @ColorStatistics, please see stats.stackexchange.com/questions/25010. | |
| Jan 25, 2019 at 20:14 | history | post merged (destination) | |||
| Jan 25, 2019 at 19:09 | history | edited | Aksakal | CC BY-SA 4.0 |
added 861 characters in body
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| Jan 25, 2019 at 18:53 | comment | added | ColorStatistics | Can you please expand on the "everything" that it encodes about the distribution? | |
| Jan 25, 2019 at 18:51 | history | answered | Aksakal | CC BY-SA 4.0 |